ABI Research: NVIDIA Leads the Fast-Growing and Complex Edge AI Chipset Market, but Competition is Intensifying

The market for edge artificial intelligence (AI) chipsets market will grow from $2.6 billion in 2019 to $7.6 billion by 2024, according to new market analysis by ABI Research.

While there is no vendor commanding more than 40% of the market, the front-runner of this market is NVIDIA, with a 39% revenue share in the first half of 2019. The GPU vendor has a strong presence in key AI verticals that are currently leading in AI deployments, such as automotive, camera systems, robotics, and smart manufacturing.

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“In the face of different use cases, NVIDIA chooses to release GPU chipsets with different computational and power budgets, said Lian Jye Su, Principal Analyst at ABI Research.. “In combination with its large developer ecosystem and partnerships with academic and research institutions, the chipset vendor has developed a strong foothold in the edge AI industry.”

However, NVIDIA is facing stiff competition from Intel with its comprehensive chipset portfolio, from Xeon CPU to Mobileye and Movidius Myriad, . At the same time, FPGA vendors, such as Xilinx, QuickLogic, and Lattice Semiconductor, are creating compelling solutions for industrial AI applications.

One missing vertical from NVIDIA’s wide footprint is consumer electronics, specifically smartphones. In recent years, AI processing in smartphones has been driven by smartphone chipset manufacturers and smartphone vendors, such as Qualcomm, Huawei, and Apple. In smart home applications, MediaTek and Amlogic are making their presence known through the widespread adoption of voice control front ends and smart appliances.

Moving forward, the AI chipset vendors will likely adopt one of three strategies:

  • Create AI chipsets that target the AI-enabled on-premise server and gateway market. Supporting enterprise use cases, these servers and gateways generally have high processing capabilities and require flexible AI chipset architecture that can support the ever-changing AI inference and training workloads.

  • Target intelligent edge devices and nodes, which, to a certain extent, favors vendors that are active in the consumer electronics space. Chipset vendors like Qualcomm and MediaTek have natural advantages here. Captive vendors who design their own AI chipsets, such as Apple, Huawei, and Samsung, have also started to broaden their AI-enabled product portfolio targeting consumer devices.

  • Target low-cost and battery-powered end devices that feature minimal computational capabilities and long useful lives. These devices are often deployed in smart cities, smart buildings, smart transportation, and utilities, all which rely on public Ethernet or Low-Power Wide-Area Networks (LPWANs) for connectivity. These “very edge” devices require lighter AI implementations, an approach often referred to as tiny or thin AI. ABI Research forecasts shipments for these devices will grow from 0.9 million in 2019 to 5.7 million in 2024, with a CAGR of 45.5%.

“The edge AI chipset market is a highly competitive one. The use cases become increasingly complex and diverse, and new players are emerging from the horizon almost monthly. Major key players have a strong heritage in building global scale for their chips, even in hugely fragmented environments. Therefore, it is crucial for the vendors, particularly newcomers, to have a clear value proposition, comprehensive software stack, and strong support from the partner ecosystem and developer community,” concluded Su.

(For more information, visit https://www.abiresearch.com)

 
Lane Cooperabi research, AI chipsets, artificial intelligence, Low-Power Wide-Area Networks, LPWAN